Non Personal Data
Non-personal data is any set of data which does not contain personally identifiable information. This means that no individual or living person can be identified by looking at such data. For example, order details collected by a food delivery service will have the name, age, gender, and other contact information of an individual, it will become non-personal data if the identifiers such as name and contact information are taken out. The government committee, which submitted its report in December 2020, has classified non-personal data into three main categories, namely public non-personal data, community non-personal data and private non-personal data.
Public non-personal data: It involves all the data collected by the government and its agencies during execution of all publicly funded works. e.g. census, data collected by municipal corporations on the total tax receipts.
Community non-personal data: It involves any data identifiers about a set of people who have either the same geographic location, religion, job, or other common social interests. e.g. The metadata collected by ride-hailing apps, telecom companies, electricity distribution companies.
Private non-personal data: It can be defined as those which are produced by individuals which can be derived from application of proprietary software or knowledge. e.g data generated by companies like Google, Amazon etc.
These data sets will help to map consumer biases and ensure targeted delivery of services. It will unlock the doors of economic value and innovation in the country.
Unlike personal data, non-personal data is more likely to be in an anonymised (without particulars or details) form. However, in certain categories such as data related to national security or strategic interests such as locations of government laboratories or research facilities, even if the data provided in anonymised form can be dangerous. Possibilities of such harm are obviously much higher if the original personal data is of a sensitive nature. Therefore, the non-personal data arising from sensitive personal data may be considered as sensitive non-personal data.
The contention here is that these data sets will heavily favour big tech companies. Only big tech companies possess the capital and infrastructure to create such large volumes of data. Others will find it difficult to match the capabilities of these technology giants.
Like many other countries, India too will have to define non-personal data in a manner that protects intellectual property rights, serves genuine public interest and promotes innovation. India can learn from France’s National Strategy on Artificial Intelligence policy, which encourages economic players to share and pool their data with the state acting as a trusted third party. France’s policy even empowers public authorities to impose openness on certain data because of its societal benefits. India can also look towards the European Union’s Regulation on the Free Flow of Non-Personal Data, which recognises the free flow of non-personal data as a prerequisite of a competitive economy.